Development and implementation of a highly-multiplexed SNP array for genetic mapping in maritime pine and comparative mapping with loblolly pine
- Equal contributors
1 INRA, UMR1202 BIOGECO, F-33610 Cestas, France
2 Université de Bordeaux, UMR1202 BIOGECO, 33170 Talence, France
3 VIB, Department of Plant Systems Biology, Gent University, Technologie park 927, B-9052 Gent, Belgium
4 Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad Universitaria, Circuito Exterior, Apartado Postal 70-275, México, D.F
5 Department of Evolution and Ecology & Center for Population Biology, University of California at Davis, Davis, CA 95616, USA
6 CEA, Institut de Génomique, Centre National de Génotypage, 2 Rue Gaston Crémieux, CP 5721, 91057 Evry Cedex, France
7 INIA, Center of Forest Research (CIFOR), E-28040 Madrid, Spain
BMC Genomics 2011, 12:368 doi:10.1186/1471-2164-12-368Published: 18 July 2011
Single nucleotide polymorphisms (SNPs) are the most abundant source of genetic variation among individuals of a species. New genotyping technologies allow examining hundreds to thousands of SNPs in a single reaction for a wide range of applications such as genetic diversity analysis, linkage mapping, fine QTL mapping, association studies, marker-assisted or genome-wide selection. In this paper, we evaluated the potential of highly-multiplexed SNP genotyping for genetic mapping in maritime pine (Pinus pinaster Ait.), the main conifer used for commercial plantation in southwestern Europe.
We designed a custom GoldenGate assay for 1,536 SNPs detected through the resequencing of gene fragments (707 in vitro SNPs/Indels) and from Sanger-derived Expressed Sequenced Tags assembled into a unigene set (829 in silico SNPs/Indels). Offspring from three-generation outbred (G2) and inbred (F2) pedigrees were genotyped. The success rate of the assay was 63.6% and 74.8% for in silico and in vitro SNPs, respectively. A genotyping error rate of 0.4% was further estimated from segregating data of SNPs belonging to the same gene. Overall, 394 SNPs were available for mapping. A total of 287 SNPs were integrated with previously mapped markers in the G2 parental maps, while 179 SNPs were localized on the map generated from the analysis of the F2 progeny. Based on 98 markers segregating in both pedigrees, we were able to generate a consensus map comprising 357 SNPs from 292 different loci. Finally, the analysis of sequence homology between mapped markers and their orthologs in a Pinus taeda linkage map, made it possible to align the 12 linkage groups of both species.
Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in maritime pine, a conifer species that has a genome seven times the size of the human genome. This SNP-array will be extended thanks to recent sequencing effort using new generation sequencing technologies and will include SNPs from comparative orthologous sequences that were identified in the present study, providing a wider collection of anchor points for comparative genomics among the conifers.